Article
Computer Science, Information Systems
Fayez Alqahtani, Mohammed Al-Maitah, Osama Elshakankiry
Summary: The mobile edge computing (MEC) paradigm provides cloud and application services, but heterogeneous services can increase delay, requiring caching and offloading features. A proactive caching technique with offloading (PCTO) can meet the needs of parallel user services, reducing response time through demand-aware offloading. Network-level caching and deep learning are used to streamline failed service distribution intervals and improve performance.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Sanaullah Manzoor, Adnan Noor Mian, Ahmed Zoha, Muhammad Ali Imran
Summary: Proactive content caching is an effective solution to handle the increasing mobile data traffic. This paper proposes a federated learning-based Mobility and Demand-aware Proactive Content Offloading (MDPCO) framework to address the limitations of existing approaches. The MDPCO utilizes distributed learning strategies and incorporates users' mobility and demand information for proactive content offloading. Simulation results demonstrate its superior performance compared to local and cloud-based models, achieving a higher data offloading ratio and improved downlink rates while being more energy-efficient.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Engineering, Electrical & Electronic
Biqian Feng, Chenyuan Feng, Daquan Feng, Yongpeng Wu, Xiang-Gen Xia
Summary: This paper aims to design a novel edge-computing-enabled hierarchical cooperative caching framework to tackle the challenges posed by the high mobility of vehicles, intermittency of information transmissions, high dynamics of user requests, limited caching capacities, and extreme complexity of business scenarios in vehicular networks. By analyzing the spatio-temporal correlation between the historical vehicle trajectory of user requests and content popularity, the system model is constructed to predict the vehicle trajectory and content popularity, which lays a foundation for mobility-aware content caching and dispatching. Privacy protection strategies are also studied to realize a privacy-preserved prediction model. Based on trajectory and popular content prediction results, content caching strategy and adaptive and dynamic resource management schemes are proposed for hierarchical cooperative caching networks. Simulations are provided to verify the effectiveness of the proposed scheme and algorithms in improving the performance of the considered system.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Qi Cheng, Hangguan Shan, Weihua Zhuang, Lu Yu, Zhaoyang Zhang, Tony Q. S. Quek
Summary: In this paper, a mobile edge computing-based streaming scheme for 360-degree mobile virtual reality video (MVRV) is proposed, which reduces end-to-end latency through video coding, proactive caching, computation offloading, and data transmission. An analytical model is also presented to study the packet transmission process and evaluate the performance.
IEEE TRANSACTIONS ON MULTIMEDIA
(2022)
Article
Computer Science, Information Systems
Jiayi Xie, Yaochen Zhu, Zhenzhong Chen
Summary: In this paper, a Hierarchical Multimodal Variational Encoder-Decoder (HMMVED) is proposed to predict the popularity of micro-videos by leveraging user information and micro-video content. The multimodal variational encoder-decoder encodes input modalities to a lower dimensional stochastic embedding to decode the popularity of micro-videos. A user encoder-decoder is designed to learn the prior Gaussian embedding of the micro-video from user information, while a micro-video encoder-decoder encodes the refined posterior distribution of the micro-video embedding from content features.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Computer Science, Hardware & Architecture
Junaid Shuja, Kashif Bilal, Waleed Alasmary, Hassan Sinky, Eisa Alanazi
Summary: Edge networking is a computing paradigm that aims to bring cloud resources closer to end users to improve responsiveness, with user mobility, preferences, and content popularity being key features. In next generation edge networks, machine learning techniques can be applied to predict content popularity and optimize cache strategies.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Telecommunications
Yingchun Wang, Jingyi Wang, Weizhan Zhang, Yufeng Zhan, Song Guo, Qinghua Zheng, Xuanyu Wang
Summary: With the rapid development of mobile devices and deep learning, mobile smart applications using deep learning technology have emerged as a main research focus. Although deep learning has achieved tremendous success in various research fields, deploying such applications on resource-restricted mobile devices remains a challenge.
DIGITAL COMMUNICATIONS AND NETWORKS
(2022)
Article
Telecommunications
Tan Li, Linqi Song
Summary: To reduce redundant data transmissions in the face of increasing multimedia traffic, mobile edge caching (MEC) plays a crucial role by equipping computation and storage capacity at the edge network. This work focuses on the cache strategy design problem in heterogeneous multi-MEC server networks with unknown content profiles. A two-step caching framework is proposed, utilizing adaptive federated learning-based estimation and effective methods for multiple objective optimizations to achieve Pareto-optimal cache placement. The theoretical results and comprehensive experiments validate the effectiveness and efficiency of the proposed approaches.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2023)
Article
Computer Science, Theory & Methods
Dewen Qiao, Songtao Guo, Defang Liu, Saiqin Long, Pengzhan Zhou, Zhetao Li
Summary: This study proposes a distributed resources-efficient proactive content caching (FPC) policy that uses federated learning and deep reinforcement learning. The adaptive FPC algorithm improves cache efficiency and reduces resource consumption.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Yan Li, Jianping Wang, Jinliang Liu
Summary: This paper proposes a game-based incentive mechanism to reward ONUs for storage contributions in order to maximize social utility or competitive individual utilities.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Jiacheng Hou, Haoye Lu, Amiya Nayak
Summary: In this study, we propose a graph neural network-gain maximization (GNN-GM) cache placement algorithm to improve user experience through caching in Named Data Networks (NDNs). By using a GNN model to predict users' ratings of unviewed videos and considering the total predicted rating as the gain of the cached video, we optimize cache placement to maximize caching gain. The experimental results show that our caching policy significantly improves cache hit ratio, latency, and server load.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Satish Kumar, Ning Wang, Yogaratnam Rahulan, Barry Evans
Summary: The integration of space information network with terrestrial infrastructures in the context of 5G, and the challenges of optimizing video segment delivery via parallel channels, were explored in this article. Systematic experiments based on real-life 5G testing framework demonstrate the effectiveness of a proposed 5G edge-computing solution in enhancing user experience and network efficiency in terms of video traffic offloading.
Article
Engineering, Electrical & Electronic
Jianhang Liu, Ning Liu, Lei Liu, Shibao Li, Hailong Zhu, Peiying Zhang
Summary: Due to limited computing resources and high upgrading costs, onboard processors alone cannot meet the quality of service requirements of emerging vehicular applications. Computation offloading is a feasible solution for computation-intensive tasks. Vehicular Collaborative Edge Computing (VCEC) aims to utilize idle computing resources of surrounding vehicles when the task density suddenly increases. However, maintaining stable task offloading performance is challenging due to high vehicle mobility and ad hoc nature of vehicular networks. Therefore, a proactive strategy is proposed to decrease performance instability events and improve task offloading performance by utilizing a mobility prediction model and an adaptive task offloading scheme based on proactive adjusting.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Telecommunications
Raghav Krishna, Varun Nayak, Vamsi Krishna Tumuluru
Summary: Proactive content caching using edge service providers (ESPs) is an emerging research topic to meet client requirements. This paper focuses on ESPs with random and time-varying storage and computing capacities, as well as uncertainties in demand and link capacities. A two-stage stochastic problem is proposed to determine content placement and demand allocation decisions, and the performance is compared to benchmark models.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2022)
Article
Telecommunications
Wei Jiang, Daquan Feng, Yao Sun, Gang Feng, Zhenzhong Wang, Xiang-Gen Xia
Summary: This research proposes an actor-critic reinforcement learning based proactive caching policy for mobile edge networks, which can minimize caching cost and expected downloading delay without prior knowledge of users' content demand. Numerical results show that the algorithm can significantly reduce total cost and average downloading delay.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2022)
Article
Automation & Control Systems
Mohammad Javad Khojasteh, Augustin A. Saucan, Zhenyu Liu, Andrea Conti, Moe Z. Win
Summary: This paper investigates how adversaries exploit location information to attack cyber-physical systems in networked environments. To prevent security breaches, a network localization and navigation (NLN) method is proposed, taking network secrecy into account in the control of mobile agents. The results show that the optimized control policy significantly improves the secrecy of the mobile agent.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Zhenyu Liu, Andrea Conti, Sanjoy K. Mitter, Moe Z. Win
Summary: This letter explores the problem of filtering over noisy channels and derives a sufficient condition to bound the estimation error. The joint design of encoder and estimator with bounded estimation error is also presented.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Bernardo Camajori Tedeschini, Monica Nicoli, Moe Z. Win
Summary: This paper proposes a Deep Autoencoding Kernel Density Model (DAKDM) for non-line-of-sight (NLOS) identification from Channel Impulse Response (CIR) data. The proposed method learns the latent distribution using a Kernel Density Estimator (KDE) in combination with a deep learning likelihood network. It has been validated in a 5G Urban micro (UMi) vehicular scenario and shows better performance compared to conventional algorithms.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Changsen Feng, Bomiao Liang, Zhengmao Li, Weijia Liu, Fushuan Wen
Summary: The wide deployment of renewable energy resources and the more proactive demand-side management have led to a new paradigm in power system operation and electricity market trading, which has boosted the emergence of the peer-to-peer market. This paper proposes a new P2P electricity trading framework with distribution network security constraints considered using the generalized fast dual ascent method. The framework includes an event-driven local P2P market and sensitivity analysis to evaluate the impacts of P2P transactions on the distribution network, ensuring secure operation.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Telecommunications
Carlos A. Gomez-Vega, Oluwatayo Y. Kolawole, Mythri Hunukumbure, Tomasz Mach, Moe Z. Win, Andrea Conti
Summary: This letter presents an experimentation and measurement campaign for outdoor device-free target detection and localization using a 5G fixed wireless access at millimeter waves (mm-Waves), namely in the 28 GHz band. Experimental results show the potential of 5G DFL at mm-Waves.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Fakhar Zaman, Saw Nang Paing, Ahmad Farooq, Hyundong Shin, Moe Z. Win
Summary: Distributed learning and multi-tier computing are crucial for achieving ultra-reliable and low-latency communication in 6G networks. The transition from connected things in 5G URLLC networks to connected intelligence in 6G URLLC networks requires secure communication due to the large amount of private data involved. This paper proposes a distributed quantum computation protocol integrated with anonymous quantum communication networks to ensure strict 6G URLLC requirements while maintaining user privacy and data security.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Fakhar Zaman, Uman Khalid, Trung Q. Duong, Hyundong Shin, Moe Z. Win
Summary: This paper proposes two new full-duplex quantum communication protocols to exchange classical or quantum information between two remote parties simultaneously without transferring a physical particle over the quantum channel. The first protocol, called quantum duplex coding, enables the exchange of a classical bit using a preshared maximally entangled pair of qubits by means of counterfactual disentanglement. The second protocol, called quantum telexchanging, enables the exchange of an arbitrary unknown qubit without using preshared entanglement by means of counterfactual entanglement and disentanglement. We demonstrate that quantum duplex coding and quantum telexchanging can be achieved by exploiting counterfactual electron-photon interaction gates. It is shown that these tasks can be viewed as full-duplex transmission of bits and qubits via binary erasure channels and quantum erasure channels, respectively.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Tra Huong Thi Le, Luiggi Cantos, Shashi Raj Pandey, Hyundong Shin, Yun Hee Kim
Summary: This study proposes a method to implement federated learning using intelligent reflecting surfaces-assisted non-orthogonal multiple access technology to reduce training latency and improve training efficiency. Furthermore, an auction-based intelligent reflecting surface allocation scheme is introduced to maximize social welfare.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Geunyeong Jang, Byungha You, In-Ho Lee, Haejoon Jung, Hyundong Shin
Summary: This article investigates the secure uplink transmissions from ground nodes to a UAV receiver using analog collaborative beamforming (ACB). The impact of UAV jitter on secrecy performance is studied, and theoretical expressions of secrecy rate in the presence and absence of jittering effects are derived. Simulation results show that ACB-based physical layer security (PLS) cannot guarantee non-zero secrecy rate, especially when an eavesdropper is in close proximity to the receiver.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Quang Nhat Le, Van-Dinh Nguyen, Octavia A. Dobre, Hyundong Shin
Summary: This letter explores the application of reconfigurable intelligent surface (RIS) in the integrated sensing and communication network. The objective is to maximize the user equipment's transmission rate by optimizing the base station's transmit beamforming, user equipment's transmit power, and RIS's phase shifts, while satisfying the condition on the minimum required sensing power.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Computer Science, Information Systems
Rojeena Bajracharya, Rakesh Shrestha, Syed Ali Hassan, Haejoon Jung, Hyundong Shin
Summary: Communication networks play a critical role in military operations, supporting various tasks such as targeting, special operations, command and control, training, and logistics. Meanwhile, commercial communication has greatly impacted society and communication methods. The emergence of 5G and beyond (5GB) networks offers high speed, low latency, reliability, and density. This paper discusses the significance of communication networks in military applications, presents communication trends, explores key performance indexes, addresses unique challenges specific to military communication networks, and discusses enabling technologies for military communication systems using 5GB.
Article
Engineering, Civil
Minh-Hien T. Nguyen, Tinh T. Bui, Long D. Nguyen, Emiliano Garcia-Palacios, Hans-Jurgen Zepernick, Hyundong Shin, Trung Q. Duong
Summary: In this paper, an optimisation problem for a satellite-supported Internet-of-Things network with cache-assisted UAVs is formulated to minimize network latency. The problem is divided into clustering, cache placement, and power allocation sub-problems, and a distributed optimization method is proposed. Simulation results show that the distributed method, although leading to higher network latency compared to the centralized method, is more efficient in terms of execution time for real-time systems and outperforms other conventional methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Optics
Stefano Marano, Moe Z. Win
Summary: This paper proposes a protocol for a quantum node to teleport multiple information-carrying qubit (ICQ) streams to different receivers using entanglements, local operations, and classical communication. The protocol establishes entangled qubit pairs (EQPs) with the receivers before the arrival of ICQs, preventing decoherence. The paper introduces the excess ratio as a quantifier of system resources per arriving ICQ and identifies the critical threshold. The work establishes the ultimate limit for distributing quantum states and introduces a protocol called fresh information delivery (FID) with proven optimality.
Article
Optics
Stefano Guerrini, Moe Z. Win, Andrea Conti
Summary: This paper introduces photon-varied quantum states (PVQSs) and provides a unified characterization method. In the special case of photon-varied Gaussian states (PVGSs), the characteristic functions and quasiprobability distributions have a simple structure. Necessary conditions for the negativity of the quasiprobability distributions for PVGSs are also obtained. This unified characterization method enables the design and analysis of quantum systems that utilize the non-Gaussian properties of PVQSs.